Simulation and parameter estimation of dynamics of synaptic depression

Abstract.

Synaptic release was simulated using a Simulink sequential storage model with three vesicular pools. Modeling was modular and easily extendable to the systems with greater number of vesicular pools, parallel input, or time-varying parameters. Given an input (short or long tetanic trains, patterned or random stimulation) and the storage model, the vesicular release, the replenishment of various vesicular pools, and the vesicular content of all pools could be simulated for the time-invariant and time-varying storage systems. From the input stimuli and either a noiseless or a noisy output, the parameters of such storage systems could also be estimated using the optimization technique that minimizes in the least square sense the error between the observed release and the predicted release. All parameters of the storage model could be evaluated with sufficiently long input–output data pairs. Not surprisingly, the parameters characterizing the processes near the release locus, such as the fractional release and the size of the immediately available pool and its coupling to the small store, as well as the state variables associated with the immediately available pool, such as its vesicular content and replenishment, could be determined with fewer stimuli. The possibility of estimating parameters with random inputs extends the applicability of the method to in vivo synapses with the physiological inputs. The parameter estimation was also possible under the time-variant, but slowly changing, conditions as well as for open systems that are part of larger vesicular storage systems but whose parameters can either not be reliably determined or are of no interest. The quality of parameter estimation was monitored continuously by comparing the observed and predicted output and/or estimated parameters with the true values. Finally, the method was tested experimentally using the rat phrenic-diaphragm neuromuscular junction.